Publications

Generally, trial and error is applied in reservoir simulation to collect some data that will be compared in finding the optimal solution of a development scenario. In this study, genetic algorithm (GA) as a directed random search technique is applied to select the optimum development scenario for X gas field production. One important parameter to be optimized in a gas field is the plateau time production. X gas field will be developed using one horizontal well. GAs role is to replace trial and error approach in finding the best horizontal well length to obtain the optimal plateau time production in X gas field.The objective function for GA is derived using curve fitting function of the plateau time towards the horizontal well length obtained from some trial cases run in the reservoir simulator. GA also will be executed for the different objective functions formulated from smaller amounts of simulation data. Smaller amounts of data represent less reservoir simulation cases run in forecasting future reservoir performance.It may be concluded at the end of this study that GA, with the appropriate objective function, can give a conformable result compared with a validation result using reservoir simulator. Moreover, the role of GA in reservoir simulation with derivation of the objective function from smaller amounts of data can still achieve accepted accuracy in finding the optimal solution for field production optimization. This method would reduce significant amounts of time in running reservoir simulation.